System Identification and Parameter Self-Tuning Controller on Deep-Sea Mining Vehicle

System identification is a quintessential measure for real-time analysis on kinematic characteristics for deep-sea mining vehicle, and thus to enhance the control performance and testing efficiency. In this study, the system identification algorithm, recursive least square method with instrumental variables(IV-RLS), is tailored to model ‘Pioneer I’, a deep-sea mining vehicle which recently completed a 1305-meter-deep sea trial in the Xisha area of the South China Sea in August, 2021. The algorithm operates on the sensor data collected from the trial to obtain the vehicle’s kinematic model and accordingly design the parameter self-tuning controller. The performances demonstrate the accuracy of the model, and prove its generalization capability. With this model, the optimal controller has been designed, the control parameters have been self-tuned, and the response time and robustness of the system have been optimized,which validates the high efficiency on digital modelling for precision control of deep-sea mining vehicles.

Research on Anti-Fluctuation Control of Winding Tension System Based on Feedforward Compensation

In the fiber winding process,strong disturbance,uncertainty,strong coupling,and fiber friction complicate the winding constant tension control.In order to effectively reduce the influence of these problems on the tension output,this paper proposed a tension fluctuation rejection strategy based on feedforward compensation.In addition to the bias harmonic curve of the unknown state,the tension fluctuation also contains the influence of bounded noise.A tension fluctuation observer(TFO)is designed to cancel the uncertain periodic signal,in which the frequency generator is used to estimate the critical parameter information.Then,the fluctuation signal is reconstructed by a third-order auxiliary filter.The estimated signal feedforward compensates for the actual tension fluctuation.Furthermore,a time-varying parameters fractional-order PID controller(TPFOPID)is realized to attenuate the bounded noise in the fluctuation.Finally,TPFOPID is enhanced by TFO and applied to control a tension control system considering multi-source disturbances.The stability of the method is analyzed by using the Lyapunov theorem.Finally,numerical simulations verify that the proposed scheme improves the tracking ability and robustness of the system in response to tension fluctuations.

Self-adapting control parameters modifieddifferential evolution for trajectoryplanning of manipulators

Control parameters of original differential evolution （DE） are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE for different optiinization problems. According to the relative position of two different individual vectors selected to generate a difference vector in the searching place, a self-adapting strategy for the scale factor F of the difference vector is proposed. In terms of the convergence status of the target vector in the current population, a self-adapting crossover probability constant CR strategy is proposed. Therefore, good target vectors have a lower CFI while worse target vectors have a large CFI. At the same time, the mutation operator is modified to improve the convergence speed. The performance of these proposed approaches are studied with the use of some benchmark problems and applied to the trajectory planning of a three-joint redundant manipulator. Finally, the experiment results show that the proposed approaches can greatly improve robustness and convergence speed.

Solution Domain Boundary Analysis Method and Its Application in Parameter Spaces of Nonlinear Gear System

Mastering the influence laws of parameters on the solution structure of nonlinear systems is the basis of carrying out vibration isolation and control.Many researches on solution structure and bifurcation phenomenon in parameter spaces are carried out broadly in many fields,and the research on nonlinear gear systems has attracted the attention of many scholars.But there is little study on the solution domain boundary of nonlinear gear systems.For a periodic non-autonomous nonlinear dynamic system with several control parameters,a solution domain boundary analysis method of nonlinear systems in parameter spaces is proposed,which combines the cell mapping method based on Poincaré point mapping in phase spaces with the domain decomposition technique of parameter spaces.The cell mapping is known as a global analysis method to analyze the global behavior of a nonlinear dynamic system with finite dimensions,and the basic idea of domain decomposition techniques is to divide and rule.The method is applied to analyze the solution domain boundaries in parameter spaces of a nonlinear gear system.The distribution of different period domains,chaos domain and the domain boundaries between different period domains and chaotic domain are obtained in control parameter spaces constituted by meshing damping ratio with excitation frequency,fluctuation coefficient of meshing stiffness and average exciting force respectively by calculation.The calculation results show that as the meshing damping increases,the responses of the system change towards a single motion,while the variations of the excitation frequency,meshing stiffness and exciting force make the solution domain presenting diversity.The proposed research contribution provides evidence for vibration control and parameter design of the gear system,and confirms the validity of the solution domain boundary analysis method.

High value of controlled attenuation parameter predicts a poor antiviral response in patients with chronic hepatits B

BACKGROUND: Controlled attenuation parameter (CAP) is a non-invasive method for diagnosing hepatic steatosis based on vibration-controlled transient elastography. The objective of this study was to investigate the effect of high value of CAP on antiviral therapy in patients with chronic hepatitis B (CHB). METHODS: Patients with CHB receiving enticavir for initial antiviral therapy were studied; they were divided into the high CAP group and normal CAP group at baseline according to the CAP values. The effect of the antiviral therapy between the two groups were compared at week 12, 24 and 48. Patients with high CAP value at baseline were divided into three subgroups, mild, moderate and severe elevation; the therapeutic response were compared among patients with normal CAP and subgroups of patients with elevated CAP. RESULTS: A total of 153 patients were enrolled. Among them, 63 were in the high CAP group and 90 in the normal CAP group. Patients with high CAP had lower rates of ALT normalization and HBV DNA clearance in response to antiviral therapy compared with those with normal CAP at week 12, 24 and 48. Further analysis showed that the rate of ALT normalization in patients with mildly and moderately elevated CAP were significant lower than those with normal CAP at week 12 and 24; while the difference was not significant between the patients with normal CAP and those with severely elevated CAP. The rate of HBV DNA clearance was significantly lower in patients with severely elevated CAP compared with those with normal CAP at week 12, 24 and 48. CONCLUSION: CHB patients with high CAP had poor response to antiviral therapy.

IMPLICIT ITERATIVE METHODS WITH VARIABLE CONTROL PARAMETERS FOR ILL-POSED OPERATOR EQUATIONS

This paper discusses a kind of implicit iterative methods with some variable parameters, which are called control parameters, for solving ill-posed operator equations. The theoretical results show that the new methods always lead to optimal convergence rates and have some other important features, especially the methods can be implemented parallelly.

Development of a Novel Feedforward Neural Network Model Based on Controllable Parameters for Predicting Effluent Total Nitrogen

The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To achieve better prediction and control of effluent TN concentration,an efficient prediction model,based on controllable operation parameters,was constructed in a sequencing batch reactor process.Compared with previous models,this model has two main characteristics:①Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability,and②the model prediction accuracy is improved on the basis of a feedforward neural network(FFNN)with algorithm optimization.The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient,and the performance was excellent compared with other models in terms of the correlation coefficient(R).The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters.This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.

Determination of temperature distribution and control parameter in a two-dimensional parabolic inverse problem with overspecified data

In this paper, we present a new algorithm to solve a two-dimensional parabolic inverse problem with a source parameter, which appears in many physical phenomena. A linearized compact difference scheme for this problem is constructed using the finite difference method. The discretization accuracy is second-order in time and fourth-order in space. We obtain the unique solvability and present an alternating direction implicit algorithm to solve this difference scheme. The results of numerical experiments are presented to demonstrate the accuracy of this algorithm.

Evaluation of controlled attenuation parameter in assessing hepatic steatosis in patients with autoimmune liver diseases

BACKGROUND Hepatic steatosis commonly occurs in some chronic liver diseases and may affect disease progression.AIM To investigate the performance of controlled attenuation parameter(CAP)for the diagnosis of hepatic steatosis in patients with autoimmune liver diseases(AILDs).METHODS Patients who were suspected of having AILDs and underwent liver biopsy were consistently enrolled.Liver stiffness measurement(LSM)and CAP were performed by transient elastography.The area under the receiver operating characteristic(AUROC)curve was used to evaluate the performance of CAP for diagnosing hepatic steatosis compared with biopsy.RESULTS Among 190 patients with biopsy-proven hepatic steatosis,69 were diagnosed with autoimmune hepatitis(AIH),18 with primary biliary cholangitis(PBC),and 27 with AIH-PBC overlap syndrome.The AUROCs of CAP for the diagnosis of steatosis in AILDS were 0.878(0.791-0.965)for S1,0.764(0.676-0.853)for S2,and 0.821(0.716-0.926)for S3.The CAP value was significantly related to hepatic steatosis grade(P<0.001).Among 69 patients with AIH,the median CAP score was 205.63±47.36 dB/m for S0,258.41±42.83 dB/m for S1,293.00±37.18 dB/m for S2,and 313.60±27.89 dB/m for S3.Compared with patients with nonalcoholic fatty liver disease(NAFLD)presenting with autoimmune markers,patients with AIH concomitant with NAFLD were much older and had higher serum IgG levels and LSM values.CONCLUSION CAP can be used as a noninvasive diagnostic method to evaluate hepatic steatosis in patients with AILDs.Determination of LSM combined with CAP may help to identify patients with AIH concomitant with NAFLD from those with NAFLD with autoimmune phenomena.

Robust sliding mode control for fractional-order chaotic economical system with parameter uncertainty and external disturbance

This paper presents a modified sliding mode control for fractional-order chaotic economical systems with parameter uncertainty and external disturbance. By constructing the suitable sliding mode surface with fractional-order integral, the effective sliding mode controller is designed to realize the asymptotical stability of fractional-order chaotic economical systems. Comparing with the existing results, the main results in this paper are more practical and rigorous. Simulation results show the effectiveness and feasibility of the proposed sliding mode control method.

Integrated Optimization of Structure and Control Parameters for the Height Control System of a Vertical Spindle Cotton Picker

Vertical picking method is a predominate method used to harvest cotton crop.However,a vertical picking method may cause spindle bending of the cotton picker if spindles collide with stones on the cotton field.Thus,how to realize a precise height control of the cotton picker is a crucial issue to be solved.The objective of this study is to design a height control system to avoid the collision.To design it,the mathematical models are established first.Then a multi-objective optimization model represented by structure parameters and control parameters is proposed to take the pressure of chamber without piston,response time and displacement error of the height control system as the opti-mization objectives.An integrated optimization approach that combines optimization via simulation,particle swarm optimization and simulated annealing is proposed to solve the model.Simulation and experimental test results show that the proposed integrated optimization approach can not only reduce the pressure of chamber without piston,but also decrease the response time and displacement error of the height control system.

Optimization of control parameters for petroleum waste composting

Composting is being widely employed in the treatment of petroleum waste. The purpose of this study was to find the optimum control parameters for petroleum waste in-vessel composting. Various physical and chemical parameters were monitored to evaluate their influence on the microbial communities present in composting. The CO2 evolution and the number of microorganisms were measured as the activity of composting. The results demonstrated that the optimum temperature, pH and moisture content were 56.5 - 59.5 degreesC, 7.0 - 8.5 and 55 % - 60%, respectively. Under the optimum conditions, the removal efficiency of petroleum hydrocarbon reached 83.29% after 30 days composting.

Scaling the Microphysics Equations and Analyzing the Variability of Hydrometeor Production Rates in a Controlled Parameter Space

A set of microphysics equations is scaled based on the convective length and velocity scales. Comparisons are made among the dynamical transport and various microphysical processes. From the scaling analysis, it becomes apparent which parameterized microphysical processes present off-scaled influences in the integration of the set of microphysics equations. The variabilities of the parameterized microphysical processes are also studied using the approach of a controlled parameter space. Given macroscopic dynamic and thermodynamic conditions in different regions of convective storms, it is possible to analyze and compare vertical profiles of these processes. Bulk diabatic heating profiles for a cumulus convective updraft and downdraft are also derived from this analysis. From the two different angles, the scale analysis and the controlled-parameter space approach can both provide an insight into and an understanding of microphysics parameterizations.

THE STUDY ON A KIND OF CONTROL SYSTEM WITH NONLINEAR PARABOLIC DISTRIBUTED PARAMETERS

The modelling of one kind of nonlinear parabolic distributed parameter control system with moving boundary, which had extensive applications was presented, Two methods were used to investigate the basic characteristics of the system: I) transforming the system it? the variable domain into that in the fixed domain; 2) transforming the distributed parameter system into the lumped parameter system. It is found that there are two critical values for the control variable : the larger one determines whether or not the boundary would move, while the smaller one determines whether or not the boundary, would atop automatically. For one-dimensional system of planar, cylindrical and spherical cases the definite solution problem can be expressed as a unified form. By means of the computer simulation the open-loop control system and close-cycle feedback control system have been investigated. Numerical results agree well with theoretical results. The computer simulation shows that the system is well posed, stable, measurable and controllable.

Simulation Study on the Controllable Dielectrophoresis Parameters of Graphene

The method of using dielectrophoresis （DEP） to assemble graphene between micro-electrodes has been proven to be simple and efficient. We present an optimization method for the kinetic formula of graphene DEP, and discuss the simulation of the graphene assembly process based on the finite element method. The simulated results illustrate that the accelerated motion of graphene is in agreement with the distribution of the electric field squared gradient. We also conduct research on the controllable parameters of the DEP assembly such as the alternating current （AC） frequency, the shape of micro-electrodes, and the ratio of the gap between electrodes to the characteristic/geometric length of graphene （λ）. The simulations based on the Clausius-Mossotti factor reveal that both graphene velocity and direction are influenced by the AC frequency. When graphene is close to the electrodes, the shape of micro-electrodes will exert great influence on the velocity of graphene. Also, λ has a great influence on the velocity of graphene. Generally, the velocity of graphene would be greater when λ is in the range of 0.4 0.6. The study is of a theoretical guiding significance in improving the precision and efficiency of the graphene DEP assembly.

A Mathematical Model of COVID-19: Analysis and Identification of Parameters for Better Decision Making

Since the onset of the COVID-19 epidemic, the world has been impressed by two things: The number of people infected and the number of deaths. Here, we propose a mathematical model of the spread of this disease, analyze this model mathematically and determine one or more dominant factors in the propagation of the COVID-19 epidemic. We consider the S-E-I-R epidemic model in the form of ordinary differential equations, in a population structured in susceptibles S, exposed E as caregivers, travelers and assistants at public events, infected I and recovered R classes. Here we decompose the recovered class into two classes: The deaths class D and the class of those who are truly healed H. After the model construction, we have calculated the basic reproduction number R0, which is a function of certain number of parameters like the size of the exposed class E. In our paper, the mathematical analysis, which consists in searching the equilibrium points and studying their stability, is done. The work identifies some parameters on which one can act to control the spread of the disease. The numerical simulations are done and they illustrate our theoretical analysis.

Multiple Elite Individual Guided Piecewise Search-Based Differential Evolution

The differential evolution(DE)algorithm relies mainly on mutation strategy and control parameters'selection.To take full advantage of top elite individuals in terms of fitness and success rates,a new mutation operator is proposed.The control parameters such as scale factor and crossover rate are tuned based on their success rates recorded over past evolutionary stages.The proposed DE variant,MIDE,performs the evolution in a piecewise manner,i.e.,after every predefined evolutionary stages,MIDE adjusts its settings to enrich its diversity skills.The performance of the MIDE is validated on two different sets of benchmarks:CEC 2014 and CEC 2017(special sessions&competitions on real-parameter single objective optimization)using different performance measures.In the end,MIDE is also applied to solve constrained engineering problems.The efficiency and effectiveness of the MIDE are further confirmed by a set of experiments.

Prospective study comparing hepatic steatosis assessment by magnetic resonance imaging and four ultrasound methods in 105 successive patients

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)is becoming a major health problem,resulting in hepatic,metabolic and cardio-vascular morbidity.AIM To evaluate new ultrasonographic tools to detect and measure hepatic steatosis.METHODS We prospectively included 105 patients referred to our liver unit for NAFLD suspicion or follow-up.They underwent ultrasonographic measurement of liver sound speed estimation(SSE)and attenuation coefficient(AC)using Aixplorer MACH 30(Supersonic Imagine,France),continuous controlled attenuation parameter(cCAP)using Fibroscan(Echosens,France)and standard liver ultrasound with hepato-renal index(HRI)calculation.Hepatic steatosis was then classified according to magnetic resonance imaging proton density fat fraction(PDFF).Receiver operating curve(ROC)analysis was performed to evaluate the diagnostic performance in the diagnosis of steatosis.RESULTS Most patients were overweight or obese(90%)and had metabolic syndrome(70%).One third suffered from diabetes.Steatosis was identified in 85 patients(81%)according to PDFF.Twenty-one patients(20%)had advanced liver disease.SSE,AC,cCAP and HRI correlated with PDFF,with respective Spearman correlation coefficient of-0.39,0.42,0.54 and 0.59(P<0.01).Area under the receiver operating characteristic curve(AUROC)for detection of steatosis with HRI was 0.91(0.83-0.99),with the best cut-off value being 1.3(Se=83%,Sp=98%).The optimal cCAP threshold of 275 dB/m,corresponding to the recent EASL-suggested threshold,had a sensitivity of 72%and a specificity of 80%.Corresponding AUROC was 0.79(0.66-0.92).The diagnostic accuracy of cCAP was more reliable when standard deviation was<15 dB/m with an AUC of 0.91(0.83-0.98).An AC threshold of 0.42 dB/cm/MHz had an AUROC was 0.82(0.70-0.93).SSE performed moderately with an AUROC of 0.73(0.62-0.84).CONCLUSION Among all ultrasonographic tools evaluated in this study,including new-generation tools such as cCAP and SSE,HRI had the best performance.It is also the simplest and most available method as most ultrasound scans are equipped with this module.

High Frequency Stability Constraints Based MMC Controller Design Using NSGA-III Algorithm

The occurrence of high frequency resonances(HFRs)has been frequently observed in several MMC-HVDC projects.To avoid these HFRs,the controller design of an MMC must satisfy two requirements:1)The controller should remain stable while in the high frequency range,and 2)MMC impedance should not possess a negative real part in the high frequency range.So far,majority of the related studies on MMC controller design have been unable to address these requirements precisely.This paper first describes the simplified high frequency MMC impedance model developed indigenously by the authors.Subsequently,the driving mechanism of two kinds of HFRs is revealed using the said developed model,including:1)MMC controller instability,and 2)Interaction instability between MMC and AC cables.Furthermore,the mathematical expressions outlining the controller stability constraint and positive damping constraint are proposed.Additionally,NSGA-III based multi-objective optimization algorithm is adopted,to identify the region most suitable for satisfying the proposed stability constraints under the MMC controller parameters.The proposed controller design method is capable of effectively evading the HFRs triggered by the incompatible MMC.The detailed time-domain simulations generated using PSCAD/EMTDC software validate the proposed designed method and endorse the improved results.

Optimal Formation Reconfiguration Control of Multiple UCAVs Using Improved Particle Swarm Optimization

Optimal formation reconfiguration control of multiple Uninhabited Combat Air Vehicles （UCAVs） is a complicated global optimum problem. Particle Swarm Optimization （PSO） is a population based stochastic optimization technique inspired by social behaviour of bird flocking or fish schooling. PSO can achieve better results in a faster, cheaper way compared with other bio-inspired computational methods, and there are few parameters to adjust in PSO. In this paper, we propose an improved PSO model for solving the optimal formation reconfiguration control problem for multiple UCAVs. Firstly, the Control Parameterization and Time Diseretization （CPTD） method is designed in detail. Then, the mutation strategy and a special mutation-escape operator are adopted in the improved PSO model to make particles explore the search space more efficiently. The proposed strategy can produce a large speed value dynamically according to the variation of the speed, which makes the algorithm explore the local and global minima thoroughly at the same time. Series experimental results demonstrate the feasibility and effectiveness of the proposed method in solving the optimal formation reconfiguration control problem for multiple UCAVs.